metric.distance.mpl {fastnet}

Median Path Length

Description

Calculate the median path length (MPL) of a network.

Usage

metric.distance.mpl(
  Network,
  probability = 0.95,
  error = 0.03,
  Cores = detectCores(),
  full = FALSE
)

Arguments

Network

The input network.

probability

The confidence level probability

error

The sampling error

Cores

Number of cores to use in the computations. By default detecCores() from parallel.

full

It calculates the sampling version by default. If it is set to true, the population MPL will be calculated and the rest of the parameters will be ignored.

Details

The median path length (MPL) is the median shortest path lengths of all pairs of nodes in Network. metric.distance.mpl(g) calculates the population MPL OR estimated MPL of network g with a sampling error set by the user. The calculation uses a parallel load balancing approach, distributing jobs equally among the cores defined by the user.

Value

A real integer

Author(s)

Luis Castro, Nazrul Shaikh.

References

E. W. Dijkstra. 1959. A note on two problems in connexion with graphs. Numer. Math. 1, 1 (December 1959), 269-271.

Castro L, Shaikh N. Estimation of Average Path Lengths of Social Networks via Random Node Pair Sampling. Department of Industrial Engineering, University of Miami. 2016.

Examples

## Not run: 
##Default function
x <-  net.erdos.renyi.gnp(1000,0.01)
metric.distance.mpl(x)
##Population MPL
metric.distance.mpl(x, full=TRUE)
##Sampling at 99% level with an error of 10% using 5 cores
metric.distance.mpl(Network = x, probability=0.99, error=0.1, Cores=5)

## End(Not run)